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Jiankang Wang. Principle of QTL mapping and inclusive composite interval mapping (ICIM)
1. 1
Principle of QTL mapping and
Inclusive Composite Interval
Mapping (ICIM)
Jiankang Wang
CIMMYT China and CAAS
E-mail: wangjk@caas.net.cn or jkwang@cgiar.org
The 9th Workshop on QTL Mapping and Breeding Simulation
The University of Sydney, Cobbitty NSW, 7-9 March 2012
2. Outlines
Quantitative traits and QTL mapping
Inclusive composite interval
mapping (ICIM) for additive and
interacting QTL
Selected publications using ICIM
The BIP functionality in QTL
IciMapping
2
4. Quantitative traits
Continuous phenotypic variation
Affected by many genes
Affected by environment
Epistasis
Polygene (or multi-factorial )
hypothesis
Classical quantitative genetics
4
5. What is QTL Mapping?
The procedure to map individual genetic factors
with small effects on the quantitative traits, to
specific chromosomal segments in the genome
The key questions in QTL mapping studies are:
How many QTL are there?
Where are they in the marker map?
How large an influence does each of them
have on the trait of interest?
5
6. 6
Dataset of QTL mapping
Mapping population
Marker data of each individual in
the mapping population
Linkage map
Phenotypic data
8. 8
Classification of mapping
populations
Bi-parental mapping populations (linkage
mapping)
Temporary population: F2 and BC
Permanent population: RIL, DH, CSSL
Secondary population
Association mapping
Natural populations: human and animals
9. 9
Overview on
QTL mapping methods
Single marker analysis (Sax 1923; Soller et al. 1976)
The single marker analysis identifies QTLs based on the difference
between the mean phenotypes for different marker groups, but cannot
separate the estimates of recombination fraction and QTL effect.
Interval mapping (IM) (Lander and Botstein 1989)
IM is based on maximum likelihood parameter estimation and provides
a likelihood ratio test for QTL position and effect. The major
disadvantage of IM is that the estimates of locations and effects of QTLs
may be biased when QTLs are linked.
Regression interval mapping (RIM)
(Haley and Knott 1992; Martinez and Curnow 1992 )
RIM was proposed to approximate maximum likelihood interval mapping
to save computation time at one or multiple genomic positions.
10. 10
Composite interval mapping (CIM) (Zeng 1994)
CIM combines IM with multiple marker regression analysis,
which controls the effects of QTLs on other intervals or
chromosomes onto the QTL that is being tested, and thus
increases the precision of QTL detection.
Multiple interval mapping (MIM) (Kao et al. 1999)
MIM is a state-of-the-art gene mapping procedure. But
implementation of the multiple-QTL model is difficult, since the
number of QTL defines the dimension of the model which is
also an unknown parameter of interest.
Bayesian model (Sillanpää and Corander 2002)
In any Bayesian model, a prior distribution has to be
considered. Based on the prior, Bayesian statistics derives the
posterior, and then conduct inference based on the posterior
distribution. However, Bayesian models have not been widely
used in practice, partially due to the complexity of
computation and the lack of user-friendly software.
11. 11
Principle of QTL mapping
Three marker types at one marker locus
A. 很可能存
在QTL和标
记的连锁
性状平均数
mm MMMm
B. 不一定存
在QTL和标
记的连锁
性状平均数
mm MMMm
12. 12
Backcrosses (P1BC1 and P2BC1)
of P1: MMQQ and P2: mmqq
BC1 BC2
Genotype Frequency
Genotypic
value
Genotype Frequency
Genotypic
value
MMQQ )1(2
1
r− m+a MmQq )1(2
1
r− m+d
MMQq r2
1
m+d Mmqq r2
1
m-a
MmQQ r2
1
m+a mmQq r2
1
m+d
MmQq )1(2
1
r− m+d mmqq )1(2
1
r− m-a
13. 13
Principle of single marker
analysis (P1BC1 as example)
Two marker types:
Difference in phenotype between the two types
MMQqMMQQMM )1( µµµ rr +−=
rdarmdmramr +−+=+++−= )1()())(1(
MmQqMmQQMm )1( µµµ rr −+=
drramdmramr )1())(1()( −++=+−++=
))(21(MmMM dar −−=− µµ
14. 14
Interval mapping (IM)
(Lander and Botstein 1989)
Linear model (j=1,2,…,n )
b* represent QTL effect, is the indicator
variable (0 or 1) for QTL genotype
Likelihood profile
Support interval: One-LOD interval
*
jx
jji exbby ++= **
0
15. 15
QTL genotypes under each marker
type in P1BC1 (double crossover not considered)
P1: P2:
F1: P1:
区间标记类型1 区间标记类型2 区间标记类型3 区间标记类型4
Mi Q Mi +1
Mi Q Mi +1
mi q mi +1
mi q mi +1
×
Mi Q Mi +1 Mi Q Mi +1
Mi Q Mi +1
×
Mi Q Mi +1 Mi Q Mi +1 Mi Q Mi +1 Mi Q Mi +1
Mi Q Mi +1 Mi Q mi +1 mi q mi q mi +1
Mi Q Mi +1
Mi q mi +1
mi q Mi +1
Mi Q Mi +1
mi Q Mi +1
mi q mi +1
Marker class I Marker class II Marker class III Marker class IV
17. 17
Problems with IM
Assumption: No more than one QTL
per chromosome or linkage group
“Ghost QTL” for linked QTL
Large confidence interval
Biased effect estimation
Composite interval mapping (CIM)
(Zeng 1994)
18. 18
Problems with CIM
In the algorithm of CIM, both QTL effect at the
current testing position and regression coefficients
of the marker variables used to control genetic
background were estimated simultaneously in an
expectation and maximization (EM) algorithm.
Thus, this algorithm could not completely ensure
that the effect of QTL at current testing interval
was not absorbed by the background marker
variables and therefore may result in biased
estimation of the QTL effect.
25. In rice
Crop Science (2008) 48: 1799-1806; Tiller
angle
Hereditas (2009) 146: 67-73; Brown
planthopper resistance
Mol. Breeding (2010) 25: 287-298; Heading
date
Scientia Agricultura Sinica 2010,43(21):
4331-4340; Nitrogen efficiency
25
26. In wheat
Euphytica (2009) 165: 435-444; flour and noodle
color components and yellow pigment content
26
27. More in wheat
Acta Agronomica Sinica (2011) 37 (2): 294-301; Coleoptile
Length and Radicle Length
Crop & Pasture Science (2009) 60: 587-597; White salted
noodle quality
Crop & Pasture Science (2011) 62: 625-638; Kernel morphology
traits
Mol. Breeding (2010) 25: 615-622; Adult-plant resistance to
powdery mildew
Theor. Appl. Genet. (2009) 119: 1349-1359; Adult-plant
resistance to stripe rust
Mol. Breeding (2011) on line published; Grain protein content
and grain yield component
Scientia Agricultura Sinica 2011,44(14):2857-2867; Grain yield
per plant and plant height
27
28. In soybean
Breeding Science
(2008) 58: 355-359 ;
Salt tolerance
ACTA
AGRONOMICA SINICA
2009, 35(12):
2139−2149; Protein
Related Traits
28
29. In Maize
Theor. Appl. Genet. (2011) 123: 327-338;
Partial restoration of male fertility of C-type
cytoplasmic male sterility
Plant Mol. Biol. Rep. (2011) on line published;
Nitrogen Use Efficiency
HEREDITAS 32(6): 625-631; The area of
leaves
29